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Aggregated data are then retrieved by external queries over the built-in data integration system.
Data stay within each data holder's privacy firewall, but data holders cooperate to convert their data into interoperable formats and respond to external queries in a privacy-compliant manner.
Federated approaches, such as the distributed annotation system (DAS) (Prlić et al., 2007) establish a central view on the data by translating each internal query into a set of external queries in order to retrieve the required data from the outside sources on the fly (Heimbigner and McLeod, 1985).
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These findings indicate the general applicability of GEM-TREND to external microarray queries independent of GEO.
Dremio believes that the self-service data access problem cannot be solved by making external, post-query copies of the data, which creates a messy problem of attempting to manage and refresh all of the copies.
We then create external data queried avatars of them according to Section 3.1 and perform predictions as per Section 3.3 using techniques in Additional file 1, Section 2.
Though some may provide facilities for batch query, the users in many instances need to employ external scripts for querying and post-processing the relevant data.
We also suggest building support for querying external binary formats into the core of a data processing pipeline to enable queries of optimized formats of data that is poorly suited for a relational database.
That approach can also be taken by external tools to query the system if those do not access the database directly.
An example of using a standard Galaxy tool to access remote resources was also briefly presented as a means to query external resources that are not Galaxy-aware.
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